Artificial intelligence in atrial fibrillation: emerging applications, research directions and ethical considerations
Atrial fibrillation (AF) is the most prevalent sustained arrhythmia and a major contributor to stroke and heart failure. Despite progress in management, challenges persist in early detection, risk stratification, and personalised treatment. Artificial intelligence (AI), especially machine learning (...
Saved in:
| Main Authors: | Ibrahim Antoun, Ahmed Abdelrazik, Mahmoud Eldesouky, Xin Li, Georgia R. Layton, Mustafa Zakkar, Riyaz Somani, G. André Ng |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-06-01
|
| Series: | Frontiers in Cardiovascular Medicine |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fcvm.2025.1596574/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
The Pathophysiology of Sex Differences in Stroke Risk and Prevention in Atrial Fibrillation: A Comprehensive Review
by: Ibrahim Antoun, et al.
Published: (2025-04-01) -
Predicting the Outcomes of External Direct Current Cardioversion for Atrial Fibrillation: A Narrative Review of Current Evidence
by: Ibrahim Antoun, et al.
Published: (2025-04-01) -
Hypertension and Atrial Fibrillation: Bridging the Gap Between Mechanisms, Risk, and Therapy
by: Ibrahim Antoun, et al.
Published: (2025-02-01) -
Role of the CHADS-VASc score in predicting hospital stay and 90-day readmission among patients with atrial fibrillation in Syria
by: Ibrahim Antoun, et al.
Published: (2025-02-01) -
Freedom of Atrial Fibrillation Predictions After Pulmonary Vein Isolation: A Review of Current Evidence
by: Ibrahim Antoun, et al.
Published: (2025-05-01)